Artificial Intelligence Navigates The London Underground

artificial intelligence london underground google AI
DeepMind's artificial intelligence uses basic reasoning to navigate the London Underground. Creative Commons

An artificial intelligence algorithm has been developed by Google's DeepMind that is capable of working out the most efficient way of getting from one point to another on London's Tube network.

The system, known as a differentiable neural computer (DNC), is able to combine basic reasoning with memory in a unique way to solve such problems.

"Like a conventional computer, it can use its memory to represent and manipulate complex data structures, but, like a neural network, it can learn to do so from the data," states a paper that details the DNC in the journal Nature.

"We show that it can learn tasks, such as finding the shortest path between specified points and inferring the missing links in randomly generated graphs, and then generalize these tasks to specific graphs, such as transport networks and family trees."

Google's DeepMind gained international media attention earlier this year after it developed the first machine capable of beating a human world champion at the board game Go.

Pointing to this achievement, leading AI expert Nick Bostrom recently said that he believed Google is leading the global race to create human-level artificial intelligence.

"There are different bets on what approach [to developing human-level AI] is most promising, and since we don't know what approach will ultimately work, there is some uncertainty there," Bostrom said at a conference in London last week.

"At this point in time, I think that DeepMind is very strong… It is probably the largest group specifically trying to solve general intelligence."